Francisco Braga is a PhD student at NOVA School of Science and Technology, working on Computer Music. Francisco obtained my Integrated Master’s degree in Electrical and Computer Engineering from Instituto Superior Técnico where he first got interested in these fields. He intends to focus on the use of emotion and structure in AI musical composition.
Alessandro Gambetti is a PhD Student of Human-Computer Interaction at the Nova School of Science and Technology in the scope of the CMU Portugal Program, Lisbon, Portugal. He received an MSc in Finance from Nova SBE, majoring in Data and Business Analytics, and he holds a BSc in Economics & Finance from the Alma Mater Università di Bologna, Bologna, Italy. His research interests span from applied data science and machine learning in human-computer interaction, information systems, as well as healthcare.
Afonso Lourenço has earned B.Sc. and M.Sc. degrees in Industrial Engineering and Management from FEUP. His research interests primarily focus on data stream mining, a field dedicated to extracting valuable insights from data that is continuously in flux.
Electric Engineering and Computer Science MSc. who has information and interaction technologies for childhood education as a main research interest. His doctoral work regards the co-design of a playful informal learning management system for primary education – a tool to help integrate everyday and implicit learning activities into educational systems and, by introducing interactive narratives set in fantastical universes starring characters to whom children are bonded by their learning, engage children in the management of these activities. The CMU Portugal program provided a unique opportunity to work with a reference scholar, and respective research group, on the topic of transformational play.
I am a CS PhD student at Nova SST, working in: Network Security, Fault Tolerant Distributed Systems, Blockchains, and Privacy-Preserving Computation. I have great interest in all aforementioned areas and aim to explore them further during my PhD, all the while finding engaging problems and trying my hand at fixing them (hopefully with some success).
In 2021 I graduated with a master’s degree in electrical and computer Engineering from Universidade de Coimbra. With a double major in automation and computers. In 2022, I was awarded a fellowship grant to join the SAFEFOREST project (a CMU-Portugal project). My research is focused on research path and motion planners, as well as develop a system using Gazebo and MoveIt (a ROS framework) to compare several path planning algorithms that help a wheeled robot navigate through an octree representation of its surroundings.
I got my B.Sc. and M.Sc. from the Department of EEE-Telecommunication Engineering of the Islamic Azad University, West Azarbaijan, Urmia Branch, and METU in EEE-Biomedical, respectively. I worked on the LFEIT project developed in the framework of TUBITAK and COST Action BM1309 and AI-Beam, and POWER – 5G RU Indoor Antenna Design projects.
I am a PhD Student in Computer Science and Engineering at Instituto Superior Técnico (Técnico), where I am very fortunate to be advised by Prof. José Fragoso Santos and Prof. Nuno Santos. I am also a junior researcher at INESC-ID, working on applying software verification and testing tools to support computer science students in their learning process. My research interests are mainly in programming languages, software verification and validation, formal methods, and cybersecurity. Previously, I completed my MSc in Computer Science and Engineering at Tecnico. My dissertation, entitled Robust Symbolic Execution for WebAssembly, was supervised by Prof. José Fragoso Santos and Prof. Nuno Santos and was defended on December 2022.
Eduardo Silva graduated in the integrated master course of biomedical engineering and is currently enrolled in the Ph.D. program in Digital Media at FEUP. With the theme “On forecasting emergency department visits”, his dissertation is focused on the construction and analysis of forecasting systems for healthcare demand in the emergency department, where it was possible to embark on the area of data science, classical or machine learning forecasting techniques, thus expanding an already vast area of knowledge.
